Specific Comic Character Detection Using Local Feature Matching
Specific Comic Character Detection Using Local Feature Matching
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DOI：
10.1109/icdar.2013.62
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发表时间：
2013-08
期刊：
影响因子：
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通讯作者：
Weihan Sun;J. Burie;J. Ogier;K. Kise
中科院分区：
文献类型：
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作者：
Weihan Sun;J. Burie;J. Ogier;K. Kise
连环画是一种以抽象线条画为主要表现形式的故事性平面出版物。漫画人物作为故事情节的线索，在故事中扮演着重要的角色，漫画人物的识别是漫画分析的重要组成部分。为此，任务包括（1）在漫画页面中定位字符和（2）识别它们，这被称为特定字符检测。对应于漫画书的不同场景，一个特定的角色可以通过各种表情来表示，再加上旋转，遮挡和其他透视图效果，这对检测提出了挑战。在本文中，我们专注于稳定的功能，关于可能的转换，并提出了一个框架来检测它们。具体地说，在训练数据集的基础上，选择一些鉴别特征作为特征字符的检测器。基于该检测器，可以检测不同场景中的相同字符的绘画。该方法已被实验和验证6标题的漫画。尽管不同场景的变化很大，所提出的方法实现了70%的漫画人物的检测。
Comic books are a kind of storytelling graphic publications mainly expressed by abstract line drawings. As a clue of story lines, comic characters play an important role in the story, and their detection is an essential part of comic book analysis. For this purpose, the task includes (1) locating characters in comics pages and (2) identifying them, which is called specific character detection. Corresponding to different scenes of comic books, one specific character can be represented by various expressions coupled with rotations, occlusions, and other perspective drawing effects, which challenge the detection. In this paper, we focus on stable features regarding the possible transformations and proposed a framework to detect them. Specifically, some discriminative features are selected as detectors for characterizing characters, on the basis of a training dataset. Based on the detectors, the drawings of the same characters in different scenes can be detected. The methodology has been experimented and validated on 6 titles of comics. Despite the terrific changes for different scenes, the proposed method achieved detection of 70% comic characters.